Linear models (Statistics)
Overview
| Works: | 115 works in 19 publications in 19 languages | |
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Titles
Applied linear statistical models : = regression, analysis of variance, and experimental designs /
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Nonlinear economic models : = cross-sectional, time series and neural network applications /
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Linear model theory : = univariate, multivariate, and mixed models /
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Generalized linear models for categorical and continuous limited dependent variables /
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The catalogue of computational material models = basic geometrically linear models in 1D /
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Effective statistical learning methods for actuaries I = GLMs and extensions /
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Applications of linear and nonlinear models = fixed effects, random effects, and total least squares /
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Modeling correlated outcomes using extensions of generalized estimating equations and linear mixed modeling
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Introduction to linear models and the design and analysis of experiments.
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Hierarchical linear models : = applications and data analysis methods /
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Multivariate statistical modelling based on generalized linear models /
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Multivariate statistical modelling based on generalized linear models /
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Multivariate statistical modelling based on generalized linear models /
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Regression modeling strategies : = with applications to linear models, logistic regression, and survival analysis /
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Advanced linear modeling : = multivariate, time series, and spatial data; nonparametric regression and response surface maximization /
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Generalized linear models : = with applications in engineering and the sciences /
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Interpreting probability models : = logit, probit, and other generalized linear models /
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Fixed effects regression methods for longitudinal data = using SAS /
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Linear Models and Generalizations = Least Squares and Alternatives /
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Recent Advances in Linear Models and Related Areas = Essays in Honour of Helge Toutenburg /
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Regression analysis : = statistical modeling of a response variable /
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Statistical modelling and regression structures = festschrift in honour of Ludwig fahrmeir /
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Advances in directional and linear statistics = a festschrift for Sreenivasa Rao Jammalamadaka /
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Generalized linear models = with applications in engineering and the sciences /
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Matrix tricks for linear statistical models : = our personal top twenty /
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A Beginner's guide to GLM and GLMM with R : = a frequentist and Bayesian perspective for ecologists /
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Vector generalized linear and additive models = with an implementation in R /
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Statistical learning with sparsity : = the lasso and generalizations /
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Bayesian data analysis in ecology using linear models withR, Bugs, and Stan
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Regression analysis : = statistical modeling of a response variable /
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